Early Stage Of Propagation Research Articles

Rapid production of recombinant rotaviruses by overexpression of NSP2 and NSP5 genes with modified nucleotide sequences.

Reverse genetics systems for rotaviruses (RV) facilitate the generation of genetically engineered RVs by transfection of 11 plasmids encoding 11 genomic viral RNA segments. In addition to viral genome expression, overexpression of NSP2 and NSP5 has been used to increase the rescue efficiency of recombinant RVs. Here, we showed that the overexpression of nucleotide sequence-modified NSP2 and NSP5 enabled the rapid and efficient production of recombinant RVs. Using improved reverse genetics, we established a reverse genetics system for human and bovine RV clinical isolates, as well as laboratory strains of bovine RV (NCDV and UK) and porcine RV (Gottfried). In addition, we rescued low-replicating recombinant RVs carrying a mutant NSP4 lacking the double-layered particle-binding domain, which was deficient in the efficient production of mature virions. These advancements in reverse genetics enabled the generation of molecular clones of RV clinical isolates and recombinant RVs harboring critical amino acid mutations, offering a versatile platform for investigating RV biology and pathogenesis.IMPORTANCERecombinant rotavirus (RV) synthesis via reverse genetics relies on both the viral propagation capacity and the efficiency of the experimental system. Since the establishment of our reverse genetics system, several enhancements have been implemented to augment the rescue efficiency. Nevertheless, challenges persist in generating RV clinical strains and recombinant viruses with low replication capacities. Notably, this improved reverse genetics system successfully facilitated the establishment of molecular clones of human and bovine RV clinical isolates. Fecal samples from patients with RV typically harbor quasi-species or, occasionally, multiple genotypes of RV. In the present study, we performed the genetic sequencing of clinical viral strains during the early propagation stages in cultured cells. Subsequently, infectious viruses were synthesized, allowing the characterization of circulating viruses in nature. This approach provides valuable insights into the genetic diversity and dynamics of RV populations and contributes to a more comprehensive understanding of viral pathogenesis and evolution.

Damage behavior of the surrounding medium caused by different blast-induced dynamic and static loadings

The combination of the dynamic action of explosion stress wave and the static action of explosion gas expansion is what primarily drives rock-breaking blasting, and their different intensities lead to different blasting effects. Therefore, experiments were conducted to explore the damage behaviour of the surrounding medium caused by different blast-induced dynamic and static loadings using digital laser Schlieren and digital laser dynamic caustic systems. The results were as follows: In the air medium, when the explosives detonated, TATP (triacetone triperoxide) had the strongest quasi-static effect, and the highest velocity explosion shock wave and products compared with those of NHN (nickel hydrazine nitrate) and DDNP (diazodinitrophenol). Part of the TATP explosion product was ahead of the shock wave front, whereas for NHN and DDNP, their explosion products were behind the propagation of the shock wave front. The highest pressure peak of TATP was the result of the combined action of the shock wave and explosion product impacting the sensor. In the solid medium, NHN, the explosive with the strongest dynamic load, had the strongest stress wave and highest stress intensity factor peak of the main crack. The velocity reached the peak value at the early stage of propagation, and the dynamic action had a dominant effect on the cracking of the crack; the stronger the dynamic action, the higher the crack initiation energy. The stress intensity factor and propagation rate of the main crack of TATP with the strongest quasi-static effect decreased slower than those of the other explosives; therefore, the main crack propagation time and length were the longest. After cracking, the quasi-static effect dominated the process of crack propagation, where the stronger the quasi-static effect, the longer duration of the driving force of crack propagation. The research results provide a basis for customising explosives for different functions in practical engineering and realising the fine and efficient utilisation of explosion energy.

Gravitational effects on large-scale premixed flame dynamics: From linear to nonlinear evolution

Gravitational effects on premixed flame propagation, coupled with Darrieus–Landau instability, are investigated through direct numerical simulations under both thermal-diffusive (TD) stable and unstable situations. During the early stage of propagation, the dispersion relation between the linear growth rate σ and wavenumber k of perturbations exhibits good symmetry, allowing it to be well-fitted by the polynomial σ=c+ak−bk2. The modified Clavin–Garcia relation derived from asymptotic analysis aligns with numerical results only in the low-wavenumber region, since the significant error in the second-order coefficient bg renders it inapplicable for the high-wavenumber region. In the nonlinear regime, three morphological effects of gravity on the flame propagation have been identified: flattening the flame front, suppressing the cusp fusion rate, and promoting the new cusp generation (front splitting). The first two effects slow down the flame propagation, respectively, by reducing the overall flame front length and delaying the appearance of velocity peaks. Nevertheless, the promotion of front splitting accelerates the flame by facilitating more frequent velocity peaks arising from both cusp generation and fusion events. These various morphological effects, along with their distinct impacts on either accelerating or decelerating the flame propagation, result in significant variations in the behavior of large-scale flame propagation under different gravitational levels, despite gravity being a large-scale stabilizing effect.

Constructing a Multivariate Linear Model to Investigate the Wind Propagation Dynamics of Dandelion with Analytic Hierarchy Process

The dandelion, a plant native to Eurasia, has successfully dispersed to regions across the globe. This dispersal is facilitated by the wind, which carries dandelion seeds attached to the pappus or petals of the pappus over considerable distances. Nevertheless, the extensive distribution of the dandelion has garnered significant attention. While this plant currently poses no immediate harm, the issue of species invasion resulting from its presence has become a matter of concern. Consequently, it is imperative to conduct research on the dissemination of the dandelion and its potential ramifications on other species. In addressing the first problem, this article commences by progressing from a rudimentary to a more intricate examination. The study dissects the wind propagation dynamics of dandelion, scrutinizing both the vertical and horizontal dimensions. It is deduced that the dandelion rapidly attains a threshold velocity during the early stages of propagation, prompting the construction of a comprehensive kinematic model for dandelion seed dispersal by integrating the analyses of both directions. Subsequently, a logarithmic distribution-based seed wind propagation model is formulated, drawing upon the aforementioned kinematic model. Lastly, the article deliberates upon the consequential ramifications. For the second problem, a multivariate linear model is developed to consider various factors including plant characteristics, environmental hazards, and ecosystem resistance. The analytic hierarchy process is employed to discuss the weight of each influencing factor and quantitatively assess the invasion ability of Taraxacum mongolicin. Ultimately, the model is tested and the collected data is utilized to verify the validity of the model.

Spatiotemporal dynamics of traffic bottlenecks yields an early signal of heavy congestions

Heavy traffic jams are difficult to predict due to the complexity of traffic dynamics. Understanding the network dynamics of traffic bottlenecks can help avoid critical large traffic jams and improve overall traffic conditions. Here, we develop a method to forecast heavy congestions based on their early propagation stage. Our framework follows the network propagation and dissipation of the traffic jams originated from a bottleneck emergence, growth, and its recovery and disappearance. Based on large-scale urban traffic-speed data, we find that dissipation duration of jams follows approximately power-law distributions, and typically, traffic jams dissolve nearly twice slower than their growth. Importantly, we find that the growth speed, even at the first 15 minutes of a jam, is highly correlated with the maximal size of the jam. Our methodology can be applied in urban traffic control systems to forecast heavy traffic bottlenecks and prevent them before they propagate to large network congestions.

3D MHD Time-dependent Charge State Ionization and Recombination Modeling of the Bastille Day Coronal Mass Ejection

Heavy ion signatures of coronal mass ejections (CMEs) indicate that rapid and strong heating takes place during the eruption and early stages of propagation. However, the nature of the heating that produces the highly ionized charge states often observed in situ is not fully constrained. An MHD simulation of the Bastille Day CME serves as a test bed to examine the origin and conditions of the formation of heavy ions evolving within the CME in connection with those observed during its passage at L1. In particular, we investigate the bimodal nature of the Fe charge state distribution, which is a quintessential heavy ion signature of CME substructure, as well as the source of the highly ionized plasma. We find that the main heating experienced by the tracked plasma structures linked to the ion signatures examined is due to field-aligned thermal conduction via shocked plasma at the CME front. Moreover, the bimodal Fe distributions can be generated through significant heating and rapid cooling of prominence material. However, although significant heating was achieved, the highest ionization stages of Fe ions observed in situ were not reproduced. In addition, the carbon and oxygen charge state distributions were not well replicated owing to anomalous heavy ion dropouts observed throughout the ejecta. Overall, the results indicate that additional ionization is needed to match observation. An important driver of ionization could come from suprathermal electrons, such as those produced via Fermi acceleration during reconnection, suggesting that the process is critical to the development and extended heating of extreme CME eruptions, like the Bastille Day CME.

SiC modified self‐healing ytterbium disilicate materials for potential environmental barrier coating application

AbstractEnvironmental barrier coatings (EBCs) are crucial to the reliability and durability of SiCf/SiC composite components seeking applications in hot sections of next‐generation advanced aero‐engines. The cracks initiated and developed in EBCs owing to various reasons during service greatly undermine their lifespans. To address this problem, in this work, silicon carbide (SiC) in the forms of particles and whiskers with various amounts have been introduced to ytterbium disilicate (Yb2Si2O7), the mainstream EBC topcoat materials, so as to gain some self‐healing potential. The results reveal that, the SiC inclusions in Yb2Si2O7 in the presence of ytterbium monosilicate (Yb2SiO5) can trigger the following reactions. Specifically, SiC self‐healing agents are oxidized to form viscous SiO2, which actively reacts with Yb2SiO5 upon encountering it, forming Yb2Si2O7. This has brought twofold beneficial effects including ① silicon supplementation of disilicate topcoat, whose silicon element tends to be “dragged out” by water vapor, leading to the deterioration of thermal mismatch; as well as ② crack self‐healing resulting from the volume expansion induced by the above reactions. Then the two aspects of self‐healing agents, namely the “promptness” and “sustainability,” have been discussed in detail. The former is unveiled to be more pertinent to the repairing of large cracks, whilst the latter is more relevant to the self‐healing of tiny cracks at initiation or early stage of propagation. The current work sheds some lights on the design and development of more durable and robust EBCs with self‐healing capability.

HG-SL: Jointly Learning of Global and Local User Spreading Behavior for Fake News Early Detection

Recently, fake news forgery technology has become more and more sophisticated, and even the profiles of participants may be faked, which challenges the robustness and effectiveness of traditional detection methods involving text or user identity. Most propagation-only approaches mainly rely on neural networks to learn the diffusion pattern of individual news, which is insufficient to describe the differences in news spread ability, and also ignores the valuable global connections of news and users, limiting the performance of detection. Therefore, we propose a joint learning model named HG-SL, which is blind to news content and user identities, but capable of catching the differences between true and fake news in the early stages of propagation through global and local user spreading behavior. Specifically, we innovatively design a Hypergraph-based Global interaction learning module to capture the global preferences of users from their co-spreading relationships, and introduce node centrality encoding to complement user influence in hypergraph learning. Moreover, the designed Self-attention-based Local context learning module first introduce spread status to highlight the propagation ability of news and users, thus providing additional signals for verifying news authenticity. Experiments on real-world datasets indicate that our HG-SL, which solely relies on user behavior, outperforms SOTA baselines utilizing multidimensional features in both fake news detection and early detection task.

Few-shot fake news detection via prompt-based tuning

As people increasingly use social media to read news, fake news has become a major problem for the public and government. One of the main challenges in fake news detection is how to identify them in the early stage of propagation. Another challenge is that detection model training requires large amounts of labeled data, which are often unavailable or expensive to acquire. To address these challenges, we propose a novel Fake News Detection model based on Prompt Tuning (FNDPT). FNDPT first designs a prompt-based template for early fake news detection. This mechanism incorporates contextual information into textual content and extracts relevant knowledge from pre-trained language models. Furthermore, our model utilizes prompt-based tuning to enhance the performance in a few-shot setting. Experimental results on two real-world datasets verify the effectiveness of FNDPT.

Persistence Augmented Graph Convolution Network for Information Popularity Prediction

In recent years, information popularity prediction of online social media plays a vital role in crisis early warning and malicious content propagation identification within public opinion management application scenarios. Existing work lacks effective mechanisms for interactive topology feature extraction among multiple correlated cascades, which contributes the propagation scale prediction especially at the early propagation stage. In this paper, we propose a Persistence augmented Graph Convolution Network framework (PT-GCN) to make popularity prediction defined as retweet number of information propagation. Persistence as the topological data analysis approach is utilized to measure and find out the salient topology structure feature. Based on it, we propose to use multi-dimensional cascade graphs to model the correlated cascades and then execute PT-GCN to form the interactive propagation features from correlated nodes in propagation and correlated cascades with persistence & contents. The performance evaluations are based on three datasets from Weibo and Twitter platform. By comparisons with the other related work, PT-GCN achieves much better efficiency in terms of MSLE and precision, which performs well for early stage propagation.

Investigation of twin growth mechanisms in precipitate hardened AZ91

In this work, an elasto-viscoplastic fast-Fourier-transform (EVP-FFT) model with a dislocation-density (DD) based hardening law is employed to study the growth of a {101¯2} tensile twin that is blocked by basal-precipitates in precipitate-hardened AZ91 magnesium alloy. It is frequently reported that twin growth is hindered in precipitate-hardened Mg alloys; however, thick twin domains are often observed experimentally in these material systems. Detailed numerical investigation of deformation twinning starting from an early propagation stage, before twin growth, reveals that the stress fields that result from two sequentially propagated twins co-impinging on a precipitate relaxes the twin back stress locally and promotes twin growth at the twin-precipitate junction. Based on these findings, a two-step growth mechanism is proposed for twins arrested by precipitates. In the first step, the interaction of a twin tip with a precipitate develops a stress concentration on the other side of the precipitate, prompting the formation of a second twin. Subsequently, the back stresses associated with the first twin are relaxed by the formation of the second twin, allowing the first twin to grow at the twin-precipitate junction and eventually engulf the precipitate. This mechanism suggests that twin growth can be achieved locally with minimal additional external forces, explaining how relatively large twin domains can develop even in the presence of arrays of precipitates.

Directional fracture behavior and stress evolution process of the multi-slit charge blasting

The multi-slit charge developed from the traditional double-slit charge has more and more engineering applications in roadway blasting and excavation. In this paper, numerical simulation and model experiments are used to compare the dynamic behaviors of double-slit/three-slit charge blasting in crack propagation, stress evolution and blasting vibration. The research results show that the directional fracture effect at the borehole middle and borehole bottom in the slit charge blasting is the best, followed by the directional fracture effect at the borehole orifice, and the length of the directional crack formed along the slit direction at the borehole middle is the largest. Compared with the double-slit charge blasting, the dynamic stress intensity factor of the directional crack at initiation stage and early propagation stage in the three-slit charge blasting is smaller, and the directional cracks formed are shorter. In addition, the effective stress evolution and blasting vibration attenuation of the gauging points along the slit direction are affected by slit number and cross-section position. The effective stress and blasting vibration of gauging points at the borehole bottom in the slit charge blasting are significantly larger than those of gauging points at the borehole orifice. For the three-slit charge blasting, the model experiment finds that the directional crack deflected to the side of protected rock mass during the propagation process. The occurrence of such deflection phenomenon is likely to cause overbreak of rock mass, which is not conducive to the formation of a straight profile surface in the rock roadway excavation.

Quantitative effects of network connectivity on epidemics

Epidemics are affected by the connectivity of nodes in networks in addition to the cooperation of infection transmission. We investigate quantitatively the effects of node connectivity on transmission dynamics by comparing epidemic diffusion in null models with gradual connection strength. Results show that: (1) the inhomogeneity of network connectivity accelerates the spreading of epidemics, this phenomenon is more significant in the early stage of propagation; (2) the enhancement of connectivity of homogenous nodes restrains epidemic spreading, and the spreading speed correlates negatively with connection strength; (3) the spreading speed of epidemics does not change linearly with the strength of rich-club property, which means that the connectivity among hub nodes does not appreciably affect disease diffusion.

Identification of vital nodes in the fake news propagation

Fake news causes an adverse effect on the regular public order and has become easier to propagate with the popularity of online social networks. The threat of fake news propagation makes it important to explore the vital nodes, which are defined as nodes with large branch sizes and hence generating a wider influence than others in this work. Previous studies about identifying vital nodes are mainly from single propagation of fake news networks, which do not consider that users may participate in different propagation networks. Here we identify vital nodes with the feature named the Ck-value that combines structural feature out-degree in a single network and multi-network user activeness. The Ck-value could reflect the branch size with a strong correlation, even at the early stage of propagation, and percolation based on Ck-value is more efficient than other indicators such as node activeness and out-degree. Thus, this research may provide a better understanding of vital nodes in the fake news propagation from topology properties, and further inspires innovative ways to identify vital nodes of fake news propagation.

A Human Flesh Search Model Based on Multiple Effects

A new model of human flesh search (HFS) was established based on the susceptible-infected-susceptible model (SIS model) and susceptible-infected-recovered model (SIR model). Four effects - impulsive effect, hot effect, herd effect and coupling effect - were proposed. In addition, the corresponding influence was investigated in the process of HFS. The results show that the impulse effect is the major factor at the early stage of propagation, and the hot effect and the herding effect play a major role at the mid-propagation. Furthermore, the coupling effect indicates that the spreading of one information fragment would be influenced by others. Moreover, the dynamic propagation rate and dynamic recovery rate were introduced; they are different from the propagation probability and recovery probability of the classical model. The propagation properties of the new model were then analyzed, and numerical simulations were performed on the small-world networks and the scale-free networks. At the same time, the validity of the new model was verified through the comparative experiment between the simulation of the proposed model and real case.

Location dependence of breathing mechanism for a slant crack in a shaft

AbstractPeriodic stresses are always imposed on a rotor, and thus, a crack due to fatigue is unavoidable. Machinery must be properly diagnosed to avoid tragic accidents. Vibration detection is the most important tool for such a diagnosis system. It is important to know the vibration characteristics of a cracked rotor in order to develop a monitoring system which can detect a crack in an early stage of propagation. In this study, to explore the crack breathing mechanism, a three‐dimensional finite element model is simulated by using a commercial analysis solver—Abaqus/Standard. A two‐disc rotor system with a slant crack is used under the coupling effect of rotor weight and unbalance force. Unlike crack breathing under rotor weight‐only, a crack opens and closes differently under the effects of unbalance forces. Crack breathing depends on its location along the length of the shaft and individual parameters of the rotor system. A few crack locations are recognised along shaft length where the crack may stay fully closed or open during shaft rotation under certain loading circumstances. These locations also split the shaft into different areas based on the orientation of the unbalance force, crack size and location, where shaft stiffness may be higher or lower. Presented findings indicate that predicting the dynamic response of cracked rotors can be anticipated much accurately. Therefore, the impacts of unbalance forces and individual rotor physical characteristics on crack breathing must be taking into consideration.

Fake news propagates differently from real news even at early stages of spreading

Social media can be a double-edged sword for society, either as a convenient channel exchanging ideas or as an unexpected conduit circulating fake news through a large population. While existing studies of fake news focus on theoretical modeling of propagation or identification methods based on machine learning, it is important to understand the realistic propagation mechanisms between theoretical models and black-box methods. Here we track large databases of fake news and real news in both, Weibo in China and Twitter in Japan from different cultures, which include their traces of re-postings. We find in both online social networks that fake news spreads distinctively from real news even at early stages of propagation, e.g. five hours after the first re-postings. Our finding demonstrates collective structural signals that help to understand the different propagation evolution of fake news and real news. Different from earlier studies, identifying the topological properties of the information propagation at early stages may offer novel features for early detection of fake news in social media.

Comparison of different turbulence models in predicting cohesive fluid mud gravity current propagation

A numerical study of propagation of cohesive fluid mud gravity currents in the form of lock-exchange was done using the OpenFOAM open source toolbox. An Eulerian approach solution for three separate phases was developed by incorporating a rheological model to predict the front position of cohesive fluid mud gravity currents. The model also simulates features in the complete movement phases including slumping, self-similar, and viscous in which the dynamics of propagation are affected by the balance of viscous and buoyancy forces, and the inertia force is negligible. The influence of using different turbulence models containing sub-grid scale (SGS), modified SGS, detached eddy simulation (DES), delayed-detached eddy simulation (DDES), Launder-R eece-Rodi (LRR), and k-ɛ models on the accuracy of simulation results was evaluated by comparing with available experimental data. The results show that the selection of the proper turbulence model is one of the most important issues for this type of the numerical modeling. The more efficient turbulence model was suggested and tabulated for each stage of propagation and different selected concentrations of 1,045, 1,140, and 1,214 g/L. Although different turbulence models (except k-ɛ) lead to front propagation dynamic simulation results that are in good agreement with the experimental measurements in the early stage of propagation for low concentrations, only DES, SGS, and modified SGS are able to capture the Kelvin-Helmholtz instability vortex shapes at the dense fluid interface, which is the main characteristic of the gravity current through the slumping phase. The calculated accuracies of SGS and modified SGS in predicting gravity current propagation for the both self-similar and viscous phases also are slightly better than DES, DDES, and LRR model results. The results of this study confirmed the performance and efficiency of the modified SGS model in which the interaction coefficients between phases are calibrated for the numerical modeling of fluid mud gravity current propagation.

In-situ investigations of hydrogen influenced crack initiation and propagation under tensile and low cycle fatigue loadings in RPV steel

Present work aims to unveil the mechanism of hydrogen embrittlement (HE) in SA508 Grade 3 Class I low alloy reactor pressure vessel (RPV) steel. In-situ tensile and low cycle fatigue (LCF) tests are performed on specially designed specimens using tensile/fatigue testing stage under scanning electron microscope (SEM). Electrochemical hydrogen charging resulted in localized void formation at prior austenite grain boundaries (PAGBs) during tensile loading. Alongside the hydrogen induced weakening of PAGBs due to synergetic HELP (hydrogen enhanced localized plasticity) and HEDE (hydrogen enhanced decohesion) mechanisms of HE, fish-eyes formation around Al2O3–SiO2 type inclusions are the primary factors for hydrogen enhanced tensile properties degradation in subject RPV steel. During LCF loading, crack initiation and propagation is facilitated by long rod inter-lath cementite particles distributed along the bainitic ferrite lath boundaries in the un-charged specimen. In case of hydrogen charged specimen, the edge crack formed during LCF loading propagated through the specimen by cleavage. Predominantly plasticity (slip) driven transgranular crack propagation occurred in un-charged specimen. In contrary, hydrogen charging resulted in LCF crack to propagate in mixed intergranular and transgranular manner during early stages of propagation, whereas once the crack length exceeded 5 to 6 grains, cleavage type transgranular crack propagation was observed.

Slickwater hydraulic fracture propagation: near-tip and radial geometry solutions

We quantify the importance of turbulent flow on the propagation of hydraulic fractures (HF) accounting for the addition of friction reducing agents to the fracturing fluid (slickwater fluid). The addition in small quantities of a high molecular weight polymer to water is sufficient to drastically reduce friction of turbulent flow. The maximum drag reduction (MDR) asymptote is always reached during industrial-like injections. The energy required for pumping is thus drastically reduced, allowing for high volume high rate hydraulic fracturing operations at a reasonable cost. We investigate the propagation of a hydraulic fracture propagating in an elastic impermeable homogeneous solid under a constant (and possibly very high) injection rate accounting for laminar and turbulent flow conditions with or without the addition of friction reducers. We solve the near-tip HF problem and estimate the extent of the laminar boundary layer near the fracture tip as a function of a tip Reynolds number for slickwater. We obtain different propagation scalings and transition time scales. This allows us to easily quantify the growth of a radial HF from the early-time turbulent regime(s) to the late-time laminar regimes. Depending on the material and injection parameters, some propagation regimes may actually be bypassed. We derive both accurate and approximate solutions for the growth of radial HF in the different limiting flow regimes (turbulent smooth, rough, MDR) for the zero fracture toughness limit (corresponding to the early stage of propagation of a radial HF). We also investigate numerically the transition(s) between the early-time MDR regime to the late-time laminar regimes (viscosity and toughness) for slickwater fluid. Our results indicate that the effect of turbulent flow on high rate slickwater HF propagation is limited and matters only at early times (at most during the first minutes for industrial hydraulic fracturing operations).